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An investigation of Forex market efficiency based on detrended fluctuation analysis: A case study for Iran

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Abstract

The efficient market hypothesis (EMH) states that asset prices fully reflect all available information. As a result, speculators cannot predict the future behavior of asset prices and earn excess profits at least after adjusting for risk. Although initial tests of the EMH were performed on stock market data, the EMH was soon applied to other markets including foreign exchange (FX). This study uses the detrended fluctuation analysis (DFA) technique to test 01:12:2005–18:04:2010 Iranian Rial/US Dollar exchange rate time series data to see if it can be explained by the weak form of the EMH. Moreover, to determine changes in the degree of inefficiency over time, the whole period has been divided into four subperiods. The study shows that the Iranian Forex market (the Rial/Dollar case) is weak-form inefficient over the whole period and in each of the subperiods. However, the degree of inefficiency is not constant over time. The findings suggest that profitable risk-adjusted trades could be made using past data.

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... A large number of studies have conducted empirical analyses of the long-range auto-correlations in several financial markets, especially the stock markets [1][2][3][4][5] and foreign exchange markets [6][7][8][9][10][11][12]. The Hurst exponent is often used to measure long-range auto-correlations in financial time series. ...
... In addition, in order to discuss the relation (12) accurately, Fig. 10 provides the difference between [H xx (q) + H yy (q)]/2 and H xy (q). From Figs. 9 and 10, we can find that H xy (q) is always less than [H xx (q) + H yy (q)]/2 for q < 0, but relation (12) does not hold for q > 0. Thus, relation (12) is not verified by empirical analysis of the Chinese exchange market and stock market. Moreover, we find that the absolute values of the difference between [H xx (q) + H yy (q)]/2 and H xy (q) are significantly larger for q < 0 than for q > 0. ...
... In addition, in order to discuss the relation (12) accurately, Fig. 10 provides the difference between [H xx (q) + H yy (q)]/2 and H xy (q). From Figs. 9 and 10, we can find that H xy (q) is always less than [H xx (q) + H yy (q)]/2 for q < 0, but relation (12) does not hold for q > 0. Thus, relation (12) is not verified by empirical analysis of the Chinese exchange market and stock market. Moreover, we find that the absolute values of the difference between [H xx (q) + H yy (q)]/2 and H xy (q) are significantly larger for q < 0 than for q > 0. ...
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... Hasan et al. [17] noticed that factors like return, market capitalization, bookto-market ratio and market value influence the share returns. Alvarez et al. [2], Abounoori et al. [1], and Kim et al. [22] observed that the efficiency degree of financial markets changes over time. To our knowledge this work is the first one that aims to study the BTC/USD market through an agent based model including realistic trading strategies. ...
... where a and b are the best fitting parameters and are equal to 1.744e + 04 and 0.002465 respectively, and the initial value of t is 1824 that corresponds to January 1st, 2014, that is the date in which our simulations start. 1 To manage the computational load of the simulation we sized the artificial market at about 1/2500 of the real market. Hence we divided by 2500 both the number of mined bitcoins per day and that of the traders. ...
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The objective of this work is to simulate the trading of the currency pair BTC/USD, investigating through the theory of the genetic algorithms the best sets of trading strategies, simulating through a realistic order book the bitcoin price formation, and reproducing a bitcoin price series that exhibits some “stylized” facts found in real-time price series In this artificial market model two kinds of agents, Chartists and Random traders, perform trading. Chartists trade through the application of trading rules. Specifically, a part of Chartists trades applying the best sets of trading rules selected by a genetic algorithm that simulates a trading system, based on four technical analysis indicators, searching for parameters of each indicator that guarantee the highest profits in the training period; the remaining part trades applying trading rules choosing their parameters in a random way. On the contrary Random Traders trade without applying any trading strategy, issuing in a random way sell or buy orders Results show that the best sets of rules found guarantee the highest profits both in the training and in the testing periods, and perform well also in the artificial market model where the Chartists who adopt the best sets of trading rules are able to achieve higher profits.
... He used Nominal Effective Exchange Rate (NEER) monthly data from 1993 to 2003. He found that the Indian forex market is weak form inefficient. Abounoori, Shahrazi and Rasekhi (2012) tested the market efficiency by using Detrended fluctuation analysis (DFA) methodology on Iranian Rial and US Dollar market. They found the weak form inefficiency in the market for whole study period. ...
... DFA has been used for dynamic analysis, among others, of heart rate variability [24], human electroencephalographic fluctuations [25] and economic and financial series [26][27][28][29][30][31][32]. In particular, DFA has been recently employed to study market efficiency [33][34][35][36][37], even though all the existing empirical studies using DFA have analysed the efficiency at specific time scales without analysing the time the market takes to achieve weak-form efficiency. This is the focus of our study. ...
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In this paper we analyse price fluctuations with the aim of measuring how long the market takes to adjust prices to weak-form efficiency, i.e., how long it takes for prices to adjust to a fractional Brownian motion with a Hurst exponent of 0.5. The Hurst exponent is estimated for different time horizons using detrended fluctuation analysis–a method suitable for non-stationary series with trends–in order to identify at which time scale the Hurst exponent is consistent with the efficient market hypothesis. Using high-frequency share price, exchange rate and stock data, we show how price dynamics exhibited important deviations from efficiency for time periods of up to 15 min; thereafter, price dynamics was consistent with a geometric Brownian motion. The intraday behaviour of the series also indicated that price dynamics at trade opening and close was hardly consistent with efficiency, which would enable investors to exploit price deviations from fundamental values. This result is consistent with intraday volume, volatility and transaction time duration patterns.
... The most efficient period was 1973-2003. Another study showing that the degree of inefficiency is not constant over time is made in [6]. IRR/USD market was inefficient over 2005-2010 and this may be caused by the negative long-range dependence, meaning that if the exchange rate is up it is likely to go down in the close future. ...
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... Often we record several variables simultaneously which exhibit long range dependence or multifractal nature. Empirical analyses of the long-range auto-correlations in several financial markets, especially the stock markets [34][35][36][37][38] and foreign exchange markets [39][40][41][42][43][44][45] have been extensively studied. To investigate long range cross-correlation between two non- stationary signals Detrended Cross Correlation Analysis (DXA) was introduced by Podobnik and Stanley as a generalization of DFA [46]. ...
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... Abounoori et al. 12 used the Detrended Fluctuation Analysis (DFA) technique to test 2005-2010 Iranian Rial/US Dollar exchange rate time series data to see if trends could be explained by the weak form of the efficient market hypothesis (EMH). Moreover, to determine changes in the degree of inefficiency over time, the whole period was divided into four sub-periods. ...
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... The persistent behavior in the time series were characterized by Detrended Fluctuation Analysis (DFA), proposed by Peng et al. [22] in their study about DNA sequences time series. The DFA method has been applied in the study of many contexts like synchronization and coordination processes in human movement [23], activity in a social network [24], music [25], chess game [26,27], and stock market data [28][29][30]. ...
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... Meanwhile, such a complex and non-stationary fluctuation has also been found in the R-R interval time series variability caused by cardiac autonomic regulation [16]. Several non-linear methods for HRV analysis are reportedly applicable in econophysics [17][18][19]. The present study addresses the implementation of this method for HRV analysis. ...
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... This ranges from the weather to the stock markets to sports events, etc. The concept of empirical forecasting has been successfully applied to various disciplines such as supply chain management [1], marketing [2], finance [3], sports [4], currency trade [5], etc., with these examples of a vast collection of works, where entire journals are dedicated to the subject. Relevant for forecasting are extreme events, 'outliers'. ...
... The examination of AMH cut across different categories of markets. For example AMH has been widely examined in the stock (Urquhart & McGroarty, 2014;Obalade and Muzindutsi, 2019a), commodity (Ramirez, Arellano & Rojas, 2015;Ghazani, Ebrahimi, 2019), digital currency (Khursheed, Naheem, Ahmed & Mustafa, 2019), bond (Charfeddine , Khediri, Aye, Gupta, 2018) and forex (Abounoori, Shahrazi, and Rasekhi, 2012) markets. From the review of studies investigating calendar anomalies under AMH, researchers found the evidence supporting the calendar effects; however, these effects appeared and disappeared. ...
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... profitable [. . . ] trades could be made using past data" (Abounoori, Shahrazi, and Raseki, 2012). Of course, on past data profit could have been made, but will the algorithm also enable profit in the future? ...
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... The key objective of focusing on forecasting or predicting the currency exchange rate between countries is to help investors, brokers, and traders through an automated system which can produce informed or guided decisions for minimizing the risk of investment along with maximizing returns on the invested amount leading to a well-produced trading strategy [1,2]. The most commonly used methods focus on: (a) purchasing power parity, the idea that there should be no purchasing and selling of the same asset in different markets to extract the best profit, which exploits the short-lived variations in the price of a similar asset in different country's markets; (b) relative economic strength, which measures the economic strength of the country with respect to their growth and is basically used to attract foreign investors; (c) econometric models, which gather the factors influencing the forecasting of exchange rates based on economic theory such as statistical and mathematical methods, and the variables which can influence the exchange rate are also taken into consideration [3,4]. ...
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Long memory property has been empirically analyzed by many researchers in stock markets.
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In this paper the point is made that most of the academic literature on the subject of private sector financial management assumes the existence of efficient capital markets. The theory of the subject, the financial strategies that result, and the recommended techniques of corporate resource allocation all revolve around efficient markets. Yet, in terms of the number of capital markets, if not in terms of the quantity of money involved, the vast majority of capital markets are not efficient.
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Brookings-Wharton Papers on Financial Services 2001 (2001) 1-45 IN A LITTLE UNDER two decades, the spread of market-oriented policies has turned the so-called lesser-developed countries into emerging markets. In 1982 the thirty-two developing-country stock markets surveyed by the International Finance Corporation (IFC) had a market capitalization of $67 billion, representing about 2.5 percent of world market capitalization. By the end of 1999, the IFC had identified eighty-one emerging stock markets with total market capitalization exceeding $3 trillion, or 8.5 percent of world equity market capitalization. In 1999 the value of outstanding domestic debt securities trading in emerging markets exceeded $1.4 trillion, representing 4.7 percent of the global bond market and a several-fold increase over the total twenty years earlier. However, bank lending to emerging markets in 1999 totaled only $783.7 billion (12 percent of consolidated international claims of banks reporting to the Bank for International Settlements), a relatively small increase over the $517.6 billion (37 percent of the total) in claims held by banks in 1980. Many forces underlie these broad trends. The debt crisis of the early 1980s cooled bankers' appetite for sovereign loans to developing nations. The financial crises in the second half of the 1990s (Mexico in 1995, Asia in 1997, and Russia in 1998, along with other hot spots) brought a fresh reminder of the perils of cross-border lending. In contrast, public financial markets for equity and debt securities were encouraged by marketoriented policies to permit private ownership of economic activities, including ownership to a larger extent by foreigners. Massive privatization programs, corporate restructuring, and financial innovations (such as global offerings and changes to the financial infrastructure) fueled the process. As dramatic as these changes have been, emerging financial markets still reflect a continuum of market conditions. Some markets are maturing and on course toward converging and integrating into the world of mature, developed financial markets. Markets in other countries are almost nonexistent or deserve the "frontier" label that the IFC gives to markets one step below emerging. This paper sketches the size and scope of financial markets in emerging nations. The focus is on the markets for foreign exchange, debt securities, equities, and bank lending in emerging nations. I present descriptive information about these markets and analyze some of the important institutional features that have affected their growth and development. Although the paper is largely descriptive, I attempt to analyze the importance of emerging financial markets, not from the standpoint of how they contribute to their own national development, but rather from the standpoint of how they contribute to the opportunities for investors and financial intermediaries in developed nations. In international economics, the gains from international trade in goods or capital often are proportional to the difference in some measure between the two trading nations. Thus the gains from trade are enhanced when there is a greater difference in relative factor endowments, relative prices, or technology on a pre-trade basis. In many respects, economists have used this concept to assess the impact of bringing emerging financial markets into the picture. The potential gains are greatest as the pre-trade marginal product of capital differs (expected value gains) or as the time pattern of asset returns differs (diversification gains from imperfect correlation in business cycles or financial market conditions). However, an argument can be made that emerging markets have paid a price for being "too different," meaning laden with idiosyncratic risks, weak institutions, and poor corporate governance. These properties discourage investors and lessen the prospects for reaping the full gains from international trade in capital. If this is the case, then emerging markets may find that their future lies in becoming more integrated into the world financial markets rather than remaining on the fringes, where they risk being marginalized. A related consideration is whether countries should attempt to reform their own institutions and markets to encourage this type of integration, or whether they should outsource many financial market activities (such as listing, clearing, and settlement) to more mature markets that have experience and credibility. The next section of this paper presents an overview...
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This paper examines the weak form efficiency of the foreign exchange markets in seven SAARC countries using monthly return series for each of these markets over a period of 21 years (1985-2005). We applied a battery of unit root tests and variance ratio tests (individual and multiple) to see whether the return series (and also the raw data) follow a random walk process. Our results suggest that the increments of the return series are not serially correlated. Therefore, we conclude that foreign exchange markets in SAARC countries are weak form efficient.
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In this paper, we investigate the fractal scaling behaviors of foreign currency exchange rates with respect to Malaysian currency, Ringgit Malaysia. These time series are examined piecewise before and after the currency control imposed in 1st September 1998 using the monofractal model based on fractional Brownian motion. The global Hurst exponents are determined using the R/S analysis, the detrended fluctuation analysis and the method of second moment using the correlation coefficients. The limitation of these monofractal analyses is discussed. The usual multifractal analysis reveals that there exists a wide range of Hurst exponents in each of the time series. A new method of modelling the multifractal time series based on multifractional Brownian motion with time-varying Hurst exponents is studied.
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In this paper we introduce two new quantifiers for the stock market inefficiency: the number of forbidden patterns and the normalized permutation entropy. They are model-independent measures, thus they have more general applicability. We find robust evidence that degree of market inefficiency is positively correlated with the number of forbidden patterns and negatively correlated with the permutation entropy. Our empirical results suggest that these two physical tools are useful to discriminate the stage of stock market development and can be easily implemented.
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It is well known that there exist statistical and structural differences between the stock markets of developed and emerging countries. In this work, and in order to find out if the efficiency of the Mexican Stock Market has been changing over time, we have performed and compared several analyses of the variations of the Mexican Stock Market index (IPC) and Dow Jones industrial average index (DJIA) for different periods of their historical daily data. We have analyzed the returns autocorrelation function (ACF) and used detrended fluctuation analysis (DFA) to study returns variations. We also analyze the volatility, mean value and standard deviation of both markets and compare their evolution. We conclude from the overall result of these studies, that they show compelling evidence of the increment of efficiency of the Mexican Stock Market over time. The data samples analyzed here, correspond to daily values of the IPC and DJIA for the period 10/30/1978–02/28/2006.
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This paper investigates the presence of fractal dynamics in stock returns. We improve upon existing literature in two ways: i) instead of rescaled-range analysis, we use the more efficient semi- nonparametric procedure suggested by Geweke and Porter-Hudak (GPH, 1983), and ii) to ensure robustness, we apply the GPH test to a variety of aggregate and sectoral stock indices and individual companies' stock returns series at both daily and monthly frequencies. Our results indicate that fractal structure is not exhibited by stock indices, but it may characterize the behavior of some individual stock returns series.
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In this paper, the efficient market hypothesis is tested for China, Hong Kong and Singapore by means of the long memory dependence approach. We find evidence suggesting that Hong Kong is the most efficient market followed by Chinese A type shares and Singapore and finally by Chinese B type shares, which suggests that liquidity and capital restrictions may play a role in explaining results of market efficiency tests.
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We analyze the European transition economics and show that many time series of major indices exhibit (i) power-law correlations in their values, (ii) power-law correlations in their magnitudes and (iii) an asymmetric probability distribution. Applying the phase randomization procedure to these time series, we show that magnitude correlations completely vanish. We propose a stochastic model that can generate time series with features (i), (ii) and (iii), and we show by means of numerical simulations that this model is capable of reproducing these three features found in the empirical data.
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There is a general consensus that forward exchange rates have little if any power as forecasts of future spot exchange rates. There is less agreement on whether forward rates contain time varying premiums. Conditional on the hypothesis that the forward market is efficient or rational, this paper finds that both components of forward rates vary through time. Moreover, most of the variation in forward rates is variation in premium, and the premium and expected future spot rate components of forward rates are negatively correlated.
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Research on this project was supported by a grant from the National Science Foundation. I am indebted to Arthur Laffer, Robert Aliber, Ray Ball, Michael Jensen, James Lorie, Merton Miller, Charles Nelson, Richard Roll, William Taylor, and Ross Watts for their helpful comments.
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We analyse the temporal changes in the cross correlations of returns on the New York Stock Exchange. We show that lead-lag relationships between daily returns of stocks vanished in less than twenty years. We have found that even for high frequency data the asymmetry of time dependent cross-correlation functions has a decreasing tendency, the position of their peaks are shifted towards the origin while these peaks become sharper and higher, resulting in a diminution of the Epps effect. All these findings indicate that the market becomes increasingly efficient.
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Whether or not currency markets may be regarded as efficient or not has been a hotly debated issue in the academic literature over recent decades. Economic theory would suggest that these markets should be efficient because they are apparently good examples of a perfectly competitive market structure. On the other hand, empirical tests of the efficient market hypothesis within these currency markets unequivocally find them to be inefficient. There is still no good explanation for this conundrum and as a result a fair amount of effort is still expended on refining the empirical studies of market efficiency, a task which is taken up in the four empirical studies that comprise this thesis. Within efficient markets, prices are predicted to respond &quotquickly" with the arrival of new information and the empirical work in the thesis focuses on these issues by identifying three key areas for research, namely, price adjustment and volatility, volatility and the &quotnews", and the speed of price adjustment. In essence, the studies examine whether there is inefficient adjustment to news in terms of excessive volatility, whether or not news is actually the main driver of exchange rate volatility and whether or not &quotquickly" can be measured empirically. The empirical results reported within this thesis confirm that the Australian dollar has not been an excessively volatile currency, even though the level of volatility has been increasing; that the pattern of information flow explains a significant degree of the non constant variance in the returns of the world's most actively traded currencies, (i.e. information explains price innovation); that the reaction time to macroeconomic news occurs within seconds of a pre-scheduled announcement, and that the bulk of adjustment to fundamental value occurs within the hour. These findings are consistent with what would be expected within an efficient market. The results reported within this thesis therefore suggest that the currency markets studied are efficient, at least for the sample periods of the data used in the studies. Exchange rates adjust rapidly with information arrival albeit not completely. It is also the case that a number of additional research questions emerge from this research. For example we know that volatility is not excessive and that it is increasing. What we do not know is the point at which increasing volatility becomes excessive. We know that exchange rates react quickly with the arrival of macroeconomic news, but we do not know precisely how long it takes for volatility to return to preannouncement levels, or why the reaction to news is inconsistent. We also do not know what type of information best explains volatility above that which is explained by the systematic dissemination of information or why full adjustment to fundamental value does not occur? Answers to these questions provide a future research agenda. Answers may provide insight that will help financial economists explain the apparent failure of the speculative efficient hypothesis.
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The study analyses the applicability of the efficient market hypothesis to the foreign exchange market by testing the profitability of the filter rule on the spot market. The significance of the returns was validated by comparing them to the returns from randomly generated shuffled series via bootstrap methods. The results were surprising. For the total period (1984-2003) small filter rules could deliver significant returns indicating an inefficient foreign exchange market. However, once the data was separated into four sub-periods of five years to test the stability of the returns, the results indicate that only the first sub period delivered significant returns. In the last two sub periods or ten years, the returns from employing filter rules were negative. This supports the conclusion that the efficient market hypothesis is valid in the foreign exchange market.
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Conclusion The main shortcomings of the EMH are similar to those of the long-run competitive theories that focus exclusively on equilibrium outcomes while ignoring the entrepreneurial activity that generates those outcomes. The EMH gives the impression that there is a difference between investing in the stock market and investing in a business. However, the stock market doesn't have alife of its own. The success or failure of investment in stocks depends ultimately on the same factors that determine success or failure of any business. Statistical tests that supposedly validate the EMH framework are based on a flawed method and a failure to understand that the main cause behind the instability in financial markets is the monetary policies of the central bank.
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Many authors have investigated the possibility of long memory in asset returns. Generally, very little evidence has been found for long memory in either stock returns or exchange rate returns. This paper applies the log-periodogram regression to a wide range of emerging market stock returns and finds some evidence for positive long memory in 7 of the 17 series considered.
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In this paper we investigate in detail the relationship between models of cointegration between the current spot exchange rate, s t , and the current forward rate, f t , and models of cointegration between the future spot rate, s t+1 , and f t and the implications of this relationship for tests of the forward rate unbiasedness hypothesis (FRUH). We argue that simple models of cointegration between s t and f t more easily capture the stylized facts of typical exchange rate data than simple models of cointegration between s t+1 and f and so serve as a natural starting point for the analysis of exchange rate behavior. We show that simple models of cointegration between s t and f t imply rather complicated models of cointegration between s t+1 and f . As a result, standard methods are often not appropriate for modeling the cointegrated behavior of (s t+1 , f t )N and we show that the use of such methods can lead to erroneous inferences regarding the FRUH. 2 1. Introduction There is an e...